Literature DB >> 34864995

Inference-based correction of multi-site height and weight measurement data in the All of Us research program.

Mirza S Khan1,2,3, Robert J Carroll3.   

Abstract

OBJECTIVE: Measurement and data entry of height and weight values are error prone. Aggregation of medical record data from multiple sites creates new challenges prompting the need to identify and correct errant values. We sought to characterize and correct issues with height and weight measurement values within the All of Us (AoU) Research Program.
MATERIALS AND METHODS: Using the AoU Researcher Workbench, we assessed site-level measurement value distributions to infer unit types. We also used plausibility checks with exceptions for conditions with possible outlier values, eg obesity, and assessed for excess deviation within individual participant's records.
RESULTS: 15.8% of height and 22.4% of weight values had missing unit type information. DISCUSSION: We identified several measurement unit related issues: the use of different units of measure within and between sites, missing units, and incorrect labeling of units. Failure to account for these in patient data repositories may lead to erroneous study results and conclusions.
CONCLUSION: Discrepancies in height and weight measurement data may arise from missing or mislabeled units. Using site- and participant-level analyses while accounting for outlier value-associated clinical conditions, we can infer measurement units and apply corrections. These methods are adaptable and expandable within AoU and other data repositories.
© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  biomedical research; body height; body mass index; body weight; electronic health records/statistics and numerical data

Mesh:

Year:  2022        PMID: 34864995      PMCID: PMC8922164          DOI: 10.1093/jamia/ocab251

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  7 in total

1.  VHA Corporate Data Warehouse height and weight data: opportunities and challenges for health services research.

Authors:  Polly Hitchcock Noël; Laurel A Copeland; Ruth A Perrin; A Elizabeth Lancaster; Mary Jo Pugh; Chen-Pin Wang; Mary J Bollinger; Helen P Hazuda
Journal:  J Rehabil Res Dev       Date:  2010

2.  A rigorous algorithm to detect and clean inaccurate adult height records within EHR systems.

Authors:  A Muthalagu; J A Pacheco; S Aufox; P L Peissig; J T Fuehrer; G Tromp; A N Kho; L J Rasmussen-Torvik
Journal:  Appl Clin Inform       Date:  2014-02-19       Impact factor: 2.342

3.  Measuring body mass index according to protocol: how are height and weight obtained?

Authors:  Jessica L J Greenwood; Scott P Narus; Jennifer Leiser; Marlene J Egger
Journal:  J Healthc Qual       Date:  2010-11-11       Impact factor: 1.095

Review 4.  Obesity and Cardiovascular Disease: A Scientific Statement From the American Heart Association.

Authors:  Tiffany M Powell-Wiley; Paul Poirier; Lora E Burke; Jean-Pierre Després; Penny Gordon-Larsen; Carl J Lavie; Scott A Lear; Chiadi E Ndumele; Ian J Neeland; Prashanthan Sanders; Marie-Pierre St-Onge
Journal:  Circulation       Date:  2021-04-22       Impact factor: 29.690

5.  The "All of Us" Research Program.

Authors:  Joshua C Denny; Joni L Rutter; David B Goldstein; Anthony Philippakis; Jordan W Smoller; Gwynne Jenkins; Eric Dishman
Journal:  N Engl J Med       Date:  2019-08-15       Impact factor: 176.079

6.  Reducing Clinical Noise for Body Mass Index Measures Due to Unit and Transcription Errors in the Electronic Health Record.

Authors:  Robert Goodloe; Eric Farber-Eger; Jonathan Boston; Dana C Crawford; William S Bush
Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2017-07-26

7.  Data model harmonization for the All Of Us Research Program: Transforming i2b2 data into the OMOP common data model.

Authors:  Jeffrey G Klann; Matthew A H Joss; Kevin Embree; Shawn N Murphy
Journal:  PLoS One       Date:  2019-02-19       Impact factor: 3.240

  7 in total
  1 in total

1.  Research data warehouse best practices: catalyzing national data sharing through informatics innovation.

Authors:  Shawn N Murphy; Shyam Visweswaran; Michael J Becich; Thomas R Campion; Boyd M Knosp; Genevieve B Melton-Meaux; Leslie A Lenert
Journal:  J Am Med Inform Assoc       Date:  2022-03-15       Impact factor: 7.942

  1 in total

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